Results for 'learning integers'

967 found
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  1. Students’ Performance and Attitude in Operating Integers Using KenKen Puzzle in a Collaborative Learning Environment.Jonathan Molina & Edwin Ibañez - 2024 - Education Digest 19 (1):45-51.
    Using the KenKen puzzle may improve students’ performance in operating integers. Quasi-experimental research was conducted to determine the effectiveness of this intervention on the performance and attitude of students in a collaborative learning environment. One hundred four purposively selected Grade 7 students in Nueva Ecija served as respondents and the experimentation lasted four days following the K to 12 Learners Manual. An increase in the student’s performance was found after utilizing the KenKen puzzle, where a significant difference between (...)
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  2. Bootstrapping of integer concepts: the stronger deviant-interpretation challenge.Markus Pantsar - 2021 - Synthese 199 (3-4):5791-5814.
    Beck presents an outline of the procedure of bootstrapping of integer concepts, with the purpose of explicating the account of Carey. According to that theory, integer concepts are acquired through a process of inductive and analogous reasoning based on the object tracking system, which allows individuating objects in a parallel fashion. Discussing the bootstrapping theory, Beck dismisses what he calls the "deviant-interpretation challenge"—the possibility that the bootstrapped integer sequence does not follow a linear progression after some point—as being general to (...)
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  3. ENHANCING GRADE 7 MATH SKILLS: AUDIO-VISUAL SIM FOR MASTERING INTEGER OPERATIONS.Matthew Cañeda, Raquel Galagala & Melrose Jemio - 2024 - Ignatian International Journal for Multidisciplinary Research 2 (10):391-404.
    This study focused on creating an Audio-Visual Strategic Intervention Material (SIM) to help Grade 7 students improve their skills in performing fundamental operations on integers in Mathematics. The research used an Educational Design Research approach and selected participants through purposive sampling. Data collection involved a checklist and rating scale, and analysis was carried out using frequency and mean. The findings revealed that mastering fundamental operations on integers had consistently been the most challenging skill for Grade 7 students during (...)
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  4. Thinking Beyond Thinking: Junior High School Students’ Metacognitive Awareness and Conceptual Understanding of Integers.Janina C. Sercenia, Edwin Ibañez & Jupeth Pentang - 2023 - Mathematics Teaching-Research Journal 15 (1):4-24.
    The potential benefits of cognitive skills in enhancing mathematics ability have been claimed by numerous researchers. Since mathematics requires a complete understanding and grasp of abstract concepts, it is essential to explore how learning with metacognitive skills affects mathematics learning. Thus, the study investigates the students' metacognitive awareness and conceptual understanding of integers. A descriptive-correlational method approach was utilized, and it was carried out on 303 seventh-grade students. The data were obtained using a metacognitive awareness inventory and (...)
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  5. How to Learn the Natural Numbers: Inductive Inference and the Acquisition of Number Concepts.Eric Margolis & Stephen Laurence - 2008 - Cognition 106 (2):924-939.
    Theories of number concepts often suppose that the natural numbers are acquired as children learn to count and as they draw an induction based on their interpretation of the first few count words. In a bold critique of this general approach, Rips, Asmuth, Bloomfield [Rips, L., Asmuth, J. & Bloomfield, A.. Giving the boot to the bootstrap: How not to learn the natural numbers. Cognition, 101, B51–B60.] argue that such an inductive inference is consistent with a representational system that clearly (...)
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  6. From Analog to Digital Computing: Is Homo sapiens’ Brain on Its Way to Become a Turing Machine?Antoine Danchin & André A. Fenton - 2022 - Frontiers in Ecology and Evolution 10:796413.
    The abstract basis of modern computation is the formal description of a finite state machine, the Universal Turing Machine, based on manipulation of integers and logic symbols. In this contribution to the discourse on the computer-brain analogy, we discuss the extent to which analog computing, as performed by the mammalian brain, is like and unlike the digital computing of Universal Turing Machines. We begin with ordinary reality being a permanent dialog between continuous and discontinuous worlds. So it is with (...)
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  7. Neutrosophic Integer Programming Problem.Mai Mohamed, Mohamed Abdel-Basset, Abdel Nasser Zaied & Florentin Smarandache - 2017 - Neutrosophic Sets and Systems 15:3-7.
    In this paper, we introduce the integer programming in neutrosophic environment, by considering coffecients of problem as a triangulare neutrosophic numbers. The degrees of acceptance, indeterminacy and rejection of objectives are simultaneously considered. The Neutrosophic Integer Programming Problem (NIP) is transformed into a crisp programming model, using truth membership (T), indeterminacy membership (I), and falsity membership (F) functions as well as single valued triangular neutrosophic numbers. To measure the efficiency of the model, we solved several numerical examples.
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  8. Learning to love the reviewer.Quan-Hoang Vuong - 2017 - European Science Editing 43 (4):83-83.
    Learning to love the reviewer -/- Issue: 43(4) November 2017. Viewpoint Page 83 -/- Quan Hoang Vuong Western University Hanoi, Centre for Interdisciplinary Social Research, Hanoi, Vietnam.
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  9. Deep learning and synthetic media.Raphaël Millière - 2022 - Synthese 200 (3):1-27.
    Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of (...)
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  10. Conjectures on Partitions of Integers As Summations of Primes.Florentin Smarandache - manuscript
    In this short note many conjectures on partitions of integers as summations of prime numbers are presented, which are extension of Goldbach conjecture.
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  11. Perceptual Learning and the Contents of Perception.Kevin Connolly - 2014 - Erkenntnis 79 (6):1407-1418.
    Suppose you have recently gained a disposition for recognizing a high-level kind property, like the property of being a wren. Wrens might look different to you now. According to the Phenomenal Contrast Argument, such cases of perceptual learning show that the contents of perception can include high-level kind properties such as the property of being a wren. I detail an alternative explanation for the different look of the wren: a shift in one’s attentional pattern onto other low-level properties. Philosophers (...)
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  12.  63
    Learning from Negativity of Experience in School Moral Education.Dariusz Stepkowski - 2024 - Theology and Philosophy of Education 3 (1):32-38.
    The paper attempts to answer the questions of what learning from negativity of experience perspective is and if it could become the right way of teaching and learning morality at school. It consists of three sections. The first one explains the fundamental distinction between negative moral experiences and negativity of moral experience. In the second section, the author’s attention focuses on the possibility of didactic application of teaching and learning from negativity of experience. The last section contains (...)
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  13. LEARNING ENVIRONMENT RELATED FACTORS AFFECTING AFGHAN EFL UNDERGRADUATES’ SPEAKING SKILL.Hazrat Usman Mashwani & Siti Maftuhah Damio - 2022 - Journal of Foreign Language Teaching and Learning (JFLTL) 7 (2):225-244.
    Of the four language skills, speaking is usually considered an indicator of proficiency in a language. As an EFL student, one should master speaking skill (Nazara, 2012). Unfortunately, most Afghan EFL undergraduates are not as good at speaking as they are in the other three English language skills (reading, writing and listening). Most Afghan undergraduate EFL learners are good at reading and writing, but in part of oral communication, they are not accurate and fluent (Zia & Sulan, 2015). Hence, this (...)
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  14. Immediate Program Learning Outcomes of Information Technology Candidates and their Introspections Towards IT Education Relevance and Global Competence Initiatives.Kannapat Kankaew, Joel Alanya-Beltran, Zaituna Khamidullina, Gilbert C. Magulod Jr, Leonilo B. Capulso, Glenn S. Cabacang, Vu Tran Anh, Leo Agustin Palapar Vela & Jupeth Pentang - 2021 - Psychology and Education 58 (2):5417-5427.
    A nation’s economy runs on the knowledge and skills of its people.Quality assurance mechanisms for higher education institutions must take cognizance of the graduates' acquisition of skills to become productive and contributory for societal development. The study is a quantitative survey assessing the attainment of the immediate program learning outcomes of the graduating Bachelor of Science in Information Technology of one campus of a public higher education institution in the Philippines. It also assessed the introspection and level of satisfaction (...)
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  15. Learning Places: Building Dwelling Thinking Online.David Kolb - 2000 - Journal of Philosophy of Education 34 (1):121-133.
    Lack of information is hardly our problem. Information comes at us in waves, sloshing out of the magazine rack, lapping at our computer monitors. It repeats and repeats on all-day news shows. It comes neatly packaged as sound bites, or little nuggets ready for trivia games. We have plenty of information, but it is not often the information we need. Even if it is, we need to learn how to deal with it. It is not just the amount, but the (...)
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  16. MACHINE LEARNING IMPROVED ADVANCED DIAGNOSIS OF SOFT TISSUES TUMORS.M. Bavadharani - 2022 - Journal of Science Technology and Research (JSTAR) 3 (1):112-123.
    Delicate Tissue Tumors (STT) are a type of sarcoma found in tissues that interface, backing, and encompass body structures. Due to their shallow recurrence in the body and their extraordinary variety, they seem, by all accounts, to be heterogeneous when seen through Magnetic Resonance Imaging (MRI). They are effortlessly mistaken for different infections, for example, fibro adenoma mammae, lymphadenopathy, and struma nodosa, and these indicative blunders have an extensive unfavorable impact on the clinical treatment cycle of patients. Analysts have proposed (...)
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  17. Perceptual Learning Explains Two Candidates for Cognitive Penetration.Valtteri Arstila - 2016 - Erkenntnis 81 (6):1151-1172.
    The cognitive penetrability of perceptual experiences has been a long-standing topic of disagreement among philosophers and psychologists. Although the notion of cognitive penetrability itself has also been under dispute, the debate has mainly focused on the cases in which cognitive states allegedly penetrate perceptual experiences. This paper concerns the plausibility of two prominent cases. The first one originates from Susanna Siegel’s claim that perceptual experiences can represent natural kind properties. If this is true, then the concepts we possess change the (...)
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  18. Perceptual learning and reasons‐responsiveness.Zoe Jenkin - 2022 - Noûs 57 (2):481-508.
    Perceptual experiences are not immediately responsive to reasons. You see a stick submerged in a glass of water as bent no matter how much you know about light refraction. Due to this isolation from reasons, perception is traditionally considered outside the scope of epistemic evaluability as justified or unjustified. Is perception really as independent from reasons as visual illusions make it out to be? I argue no, drawing on psychological evidence from perceptual learning. The flexibility of perceptual learning (...)
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  19. Machine Learning-Based Diabetes Prediction: Feature Analysis and Model Assessment.Fares Wael Al-Gharabawi & Samy S. Abu-Naser - 2023 - International Journal of Academic Engineering Research (IJAER) 7 (9):10-17.
    This study employs machine learning to predict diabetes using a Kaggle dataset with 13 features. Our three-layer model achieves an accuracy of 98.73% and an average error of 0.01%. Feature analysis identifies Age, Gender, Polyuria, Polydipsia, Visual blurring, sudden weight loss, partial paresis, delayed healing, irritability, Muscle stiffness, Alopecia, Genital thrush, Weakness, and Obesity as influential predictors. These findings have clinical significance for early diabetes risk assessment. While our research addresses gaps in the field, further work is needed to (...)
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  20. Perceptual learning.Zoe Jenkin - 2023 - Philosophy Compass 18 (6):e12932.
    Perception provides us with access to the external world, but that access is shaped by our own experiential histories. Through perceptual learning, we can enhance our capacities for perceptual discrimination, categorization, and attention to salient properties. We can also encode harmful biases and stereotypes. This article reviews interdisciplinary research on perceptual learning, with an emphasis on the implications for our rational and normative theorizing. Perceptual learning raises the possibility that our inquiries into topics such as epistemic justification, (...)
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  21. Learning Motivation and Utilization of Virtual Media in Learning Mathematics.Almighty Tabuena & Jupeth Pentang - 2021 - Asia-Africa Journal of Recent Scientific Research 1 (1):65-75.
    This study aims to describe the learning motivation of students using virtual media when they are learning mathematics in grade 5. The research design applied in this research is classroom action research. The research is conducted in two phases which involve planning, action and observation and reflection. The results of the study revealed that intrinsic motivation to learn is most prevalent in the form of fun to learn mathematics with virtual media. Other forms of intrinsic motivation include curiosity, (...)
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  22. Bayesian Learning Models of Pain: A Call to Action.Abby Tabor & Christopher Burr - 2019 - Current Opinion in Behavioral Sciences 26:54-61.
    Learning is fundamentally about action, enabling the successful navigation of a changing and uncertain environment. The experience of pain is central to this process, indicating the need for a change in action so as to mitigate potential threat to bodily integrity. This review considers the application of Bayesian models of learning in pain that inherently accommodate uncertainty and action, which, we shall propose are essential in understanding learning in both acute and persistent cases of pain.
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  23. Learning Organizations and Their Role in Achieving Organizational Excellence in the Palestinian Universities.Mazen J. Al Shobaki, Samy S. Abu Naser, Youssef M. Abu Amuna & Amal A. Al Hila - 2017 - International Journal of Digital Publication Technology 1 (2):40-85.
    The research aims to identify the learning organizations and their role in achieving organizational excellence in the Palestinian universities in Gaza Strip. The researchers used descriptive analytical approach and used the questionnaire as a tool for information gathering. The questionnaires were distributed to senior management in the Palestinian universities. The study population reached (344) employees in senior management is dispersed over (3) Palestinian universities. A stratified random sample of (182) workers from the Palestinian universities was selected and the recovery (...)
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  24. Kronecker, God and the Integers.A. P. Bird - 2021 - Cantor's Paradise (00):3.
    Leopold Kronecker (1823–1891) was a German mathematician who worked on number theory and algebra. He is considered a pre-intuitionist, being only close to intuitionism because he rejected Cantor’s Set Theory. He was, in fact, more radical than the intuitionists. Unlike Poincaré, for example, Kronecker didn’t accept the transfinite numbers as valid mathematical entities.
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  25. On Certain Axiomatizations of Arithmetic of Natural and Integer Numbers.Urszula Wybraniec-Skardowska - 2019 - Axioms 2019 (Deductive Systems).
    The systems of arithmetic discussed in this work are non-elementary theories. In this paper, natural numbers are characterized axiomatically in two di erent ways. We begin by recalling the classical set P of axioms of Peano’s arithmetic of natural numbers proposed in 1889 (including such primitive notions as: set of natural numbers, zero, successor of natural number) and compare it with the set W of axioms of this arithmetic (including the primitive notions like: set of natural numbers and relation of (...)
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  26. Modular Learning Efficiency: Learner’s Attitude and Performance Towards Self-Learning Modules.April Clarice C. Bacomo, Lucy P. Daculap, Mary Grace O. Ocampo, Crystalyn D. Paguia, Jupeth Pentang & Ronalyn M. Bautista - 2022 - IOER International Multidisciplinary Research Journal 4 (2):60-72.
    Learner’s attitude towards modular distance learning catches uncertainties as a world crisis occurs up to this point. As self-learning modules (SLMs) become a supplemental means of learning in new normal education, this study investigated efficiency towards the learners’ attitude and performance. Specifically, the study described the learners’ profile and their attitude and performance towards SLMs. It also ascertained the relationship between the learner’s profile with their attitude and performance, as well as the relationship between attitude and performance (...)
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  27. Distributed learning: Educating and assessing extended cognitive systems.Richard Heersmink & Simon Knight - 2018 - Philosophical Psychology 31 (6):969-990.
    Extended and distributed cognition theories argue that human cognitive systems sometimes include non-biological objects. On these views, the physical supervenience base of cognitive systems is thus not the biological brain or even the embodied organism, but an organism-plus-artifacts. In this paper, we provide a novel account of the implications of these views for learning, education, and assessment. We start by conceptualising how we learn to assemble extended cognitive systems by internalising cultural norms and practices. Having a better grip on (...)
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  28. Learning Incommensurate Concepts.Hayley Clatterbuck & Hunter Gentry - forthcoming - Synthese.
    A central task of developmental psychology and philosophy of science is to show how humans learn radically new concepts. Famously, Fodor has argued that such learning is impossible if concepts have definitional structure and all learning is hypothesis testing. We present several learning processes that can generate novel concepts. They yield transformations of the fundamental feature space, generating new similarity structures which can underlie conceptual change. This framework provides a tractable, empiricist-friendly account that unifies and shores up (...)
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  29. Learning to Discriminate: The Perfect Proxy Problem in Artificially Intelligent Criminal Sentencing.Benjamin Davies & Thomas Douglas - 2022 - In Jesper Ryberg & Julian V. Roberts (eds.), Sentencing and Artificial Intelligence. Oxford: OUP.
    It is often thought that traditional recidivism prediction tools used in criminal sentencing, though biased in many ways, can straightforwardly avoid one particularly pernicious type of bias: direct racial discrimination. They can avoid this by excluding race from the list of variables employed to predict recidivism. A similar approach could be taken to the design of newer, machine learning-based (ML) tools for predicting recidivism: information about race could be withheld from the ML tool during its training phase, ensuring that (...)
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  30. The Use of Machine Learning Methods for Image Classification in Medical Data.Destiny Agboro - forthcoming - International Journal of Ethics.
    Integrating medical imaging with computing technologies, such as Artificial Intelligence (AI) and its subsets: Machine learning (ML) and Deep Learning (DL) has advanced into an essential facet of present-day medicine, signaling a pivotal role in diagnostic decision-making and treatment plans (Huang et al., 2023). The significance of medical imaging is escalated by its sustained growth within the realm of modern healthcare (Varoquaux and Cheplygina, 2022). Nevertheless, the ever-increasing volume of medical images compared to the availability of imaging experts. (...)
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  31. (1 other version)Machine Learning and Irresponsible Inference: Morally Assessing the Training Data for Image Recognition Systems.Owen C. King - 2019 - In Matteo Vincenzo D'Alfonso & Don Berkich (eds.), On the Cognitive, Ethical, and Scientific Dimensions of Artificial Intelligence. Springer Verlag. pp. 265-282.
    Just as humans can draw conclusions responsibly or irresponsibly, so too can computers. Machine learning systems that have been trained on data sets that include irresponsible judgments are likely to yield irresponsible predictions as outputs. In this paper I focus on a particular kind of inference a computer system might make: identification of the intentions with which a person acted on the basis of photographic evidence. Such inferences are liable to be morally objectionable, because of a way in which (...)
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  32. E-Learning Strategies in Developing Research Performance Efficiency: Higher Education Institutions.Samia A. M. Abdalmenem, Samer M. Arqawi, Youssef M. Abu Amuna, Samy S. Abu Naser & Mazen J. Al Shobaki - 2019 - International Journal of Academic Pedagogical Research (IJAPR) 3 (9):8-19.
    The study aimed to identify E- Learning strategies and their relation to the efficiency of research performance in foreign and Palestinian universities (University of Ottawa, Munster, Suez Canal, Al-Azhar, Islamic, Al-Aqsa). The analytical descriptive approach was used for this purpose, and relying on the questionnaire as a main tool for data collection. The study society is from the senior management, where the number of senior management in the universities in question is 206. The random stratified sample was selected and (...)
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  33. Learning Networks and Connective Knowledge.Stephen Downes - 2010 - In Harrison Hao Yang & Steve Chi-Yin Yuen (eds.), Collective Intelligence and E-Learning 2.0: Implications of Web-Based Communities and Networking. IGI Global.
    The purpose of this chapter is to outline some of the thinking behind new e-learning technology, including e-portfolios and personal learning environments. Part of this thinking is centered around the theory of connectivism, which asserts that knowledge - and therefore the learning of knowledge - is distributive, that is, not located in any given place (and therefore not 'transferred' or 'transacted' per se) but rather consists of the network of connections formed from experience and interactions with a (...)
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  34. Clinical applications of machine learning algorithms: beyond the black box.David S. Watson, Jenny Krutzinna, Ian N. Bruce, Christopher E. M. Griffiths, Iain B. McInnes, Michael R. Barnes & Luciano Floridi - 2019 - British Medical Journal 364:I886.
    Machine learning algorithms may radically improve our ability to diagnose and treat disease. For moral, legal, and scientific reasons, it is essential that doctors and patients be able to understand and explain the predictions of these models. Scalable, customisable, and ethical solutions can be achieved by working together with relevant stakeholders, including patients, data scientists, and policy makers.
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  35.  23
    Revolutionizing Agriculture with Deep Learning-Based Plant Health Monitoring.P. Selvaprasanth - 2024 - Journal of Science Technology and Research (JSTAR) 5 (1):655-666.
    By leveraging convolutional neural networks (CNNs), the model identifies various plant diseases with high accuracy. The experimental setup includes a dataset consisting of healthy and diseased leaf images of different plant species. The dataset is preprocessed to remove noise and augmented to address the issue of class imbalance. The CNN model is then trained, validated, and tested on this dataset. The results indicate that the deep learning model achieves a classification accuracy of over 95% for most plant diseases. Additionally, (...)
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  36. STUDENTS’ DEMOTIVATION IN LEARNING ENGLISH AS A SECOND LANGUAGE.Shirley D. Dangan - 2023 - Get International Research Journal 1 (2):125–131.
    Students with high motivation to learn English as a second language become efficient language learners and ultimately acquire second language proficiency. However, demotivation in learning English as a second language remains to be a serious challenge. Thus, research-based information is needed to shed light in unravelling the factors of demotivation among second language learners and to guide teachers in putting forward practical solutions to increase students’ motivation in second language learning. This study was conducted to find out the (...)
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  37. Networked Learning and Three Promises of Phenomenology.Lucy Osler - forthcoming - In Phenomenology in Action for Researching Networked Learning Experiences.
    In this chapter, I consider three ‘promises’ of bringing phenomenology into dialogue with networked learning. First, a ‘conceptual promise’, which draws attention to conceptual resources in phenomenology that can inspire and inform how we understand, conceive of, and uncover experiences of participants in networked learning activities and environments. Second, a ‘methodological promise’, which outlines a variety of ways that phenomenological methodologies and concepts can be put to use in empirical research in networked learning. And third, a ‘critical (...)
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  38. Learning Computer Networks Using Intelligent Tutoring System.Mones M. Al-Hanjori, Mohammed Z. Shaath & Samy S. Abu Naser - 2017 - International Journal of Advanced Research and Development 2 (1).
    Intelligent Tutoring Systems (ITS) has a wide influence on the exchange rate, education, health, training, and educational programs. In this paper we describe an intelligent tutoring system that helps student study computer networks. The current ITS provides intelligent presentation of educational content appropriate for students, such as the degree of knowledge, the desired level of detail, assessment, student level, and familiarity with the subject. Our Intelligent tutoring system was developed using ITSB authoring tool for building ITS. A preliminary evaluation of (...)
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  39. Learning Concepts: A Learning-Theoretic Solution to the Complex-First Paradox.Nina Laura Poth & Peter Brössel - 2020 - Philosophy of Science 87 (1):135-151.
    Children acquire complex concepts like DOG earlier than simple concepts like BROWN, even though our best neuroscientific theories suggest that learning the former is harder than learning the latter and, thus, should take more time (Werning 2010). This is the Complex- First Paradox. We present a novel solution to the Complex-First Paradox. Our solution builds on a generalization of Xu and Tenenbaum’s (2007) Bayesian model of word learning. By focusing on a rational theory of concept learning, (...)
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  40. Learning Management System (LMS) for Academic Inclusion and Learning Agency: An Interpretive Review of Technoprogressivism in ODL Instructional Technology Policy.Bongani Nkambule, Sindile Ngubane & Siphamandla Mncube - 2023 - Journal of Education Society and Multiculturalism 4 (2):48-84.
    Literature frequently describes how ineffective implementation of instructional policy frameworks can make distance learning a lonely and unrewarding academic pursuit, characterized by high student drop-out rates, high failure rates and academic exclusion. In trying to mitigate this catastrophe, academic departments in distance learning institutions utilize learning management systems (LMSs) to stimulate students’ learning experiences. In keeping with techno-progressivism, the researchers (and authors of this paper) turned to extant documentary policy and literature to review – qualitatively – (...)
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  41. Learning in Lithic Landscapes: A Reconsideration of the Hominid “Toolmaking” Niche.Peter Hiscock - 2014 - Biological Theory 9 (1):27-41.
    This article reconsiders the early hominid ‘‘lithic niche’’ by examining the social implications of stone artifact making. I reject the idea that making tools for use is an adequate explanation of the elaborate artifact forms of the Lower Palaeolithic, or a sufficient cause for long-term trends in hominid technology. I then advance an alternative mechanism founded on the claim that competency in making stone artifacts requires extended learning, and that excellence in artifact making is attained only by highly skilled (...)
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  42. The Learning-Consciousness Connection.Jonathan Birch, Simona Ginsburg & Eva Jablonka - 2021 - Biology and Philosophy 36 (5):1-14.
    This is a response to the nine commentaries on our target article “Unlimited Associative Learning: A primer and some predictions”. Our responses are organized by theme rather than by author. We present a minimal functional architecture for Unlimited Associative Learning that aims to tie to together the list of capacities presented in the target article. We explain why we discount higher-order thought theories of consciousness. We respond to the criticism that we have overplayed the importance of learning (...)
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  43. Deep Learning as Method-Learning: Pragmatic Understanding, Epistemic Strategies and Design-Rules.Phillip H. Kieval & Oscar Westerblad - manuscript
    We claim that scientists working with deep learning (DL) models exhibit a form of pragmatic understanding that is not reducible to or dependent on explanation. This pragmatic understanding comprises a set of learned methodological principles that underlie DL model design-choices and secure their reliability. We illustrate this action-oriented pragmatic understanding with a case study of AlphaFold2, highlighting the interplay between background knowledge of a problem and methodological choices involving techniques for constraining how a model learns from data. Building successful (...)
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  44. Amidst the Online Learning Modality: The Social Support and Its Relationship to the Anxiety of Senior High School Students.Jastine Joy Basilio, Twinkle Pangilinan, Jeremiah Joy Kalong & Jhoselle Tus - 2022 - Psychology Abd Education: A Multidisciplinary Journal 1 (1):1-6.
    Senior high school is known to be part of the newly implemented K-12 program in the Philippines' educational system. Hence, this program added two years to the academic learning program of students, which mainly focuses on different theoretical and vocational strands that aim to prepare and fully furnish the students for education and employment in the future. Due to adjustments to new online learning amidst the pandemic, students begin to experience various challenges, primarily social support and mental well-being. (...)
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  45. Learning, evolvability and exploratory behaviour: extending the evolutionary reach of learning.Rachael L. Brown - 2013 - Biology and Philosophy 28 (6):933-955.
    Traditional accounts of the role of learning in evolution have concentrated upon its capacity as a source of fitness to individuals. In this paper I use a case study from invasive species biology—the role of conditioned taste aversion in mitigating the impact of cane toads on the native species of Northern Australia—to highlight a role for learning beyond this—as a source of evolvability to populations. This has two benefits. First, it highlights an otherwise under-appreciated role for learning (...)
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  46. Learning from Conditionals.Benjamin Eva, Stephan Hartmann & Soroush Rafiee Rad - 2020 - Mind 129 (514):461-508.
    In this article, we address a major outstanding question of probabilistic Bayesian epistemology: how should a rational Bayesian agent update their beliefs upon learning an indicative conditional? A number of authors have recently contended that this question is fundamentally underdetermined by Bayesian norms, and hence that there is no single update procedure that rational agents are obliged to follow upon learning an indicative conditional. Here we resist this trend and argue that a core set of widely accepted Bayesian (...)
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  47. Learning and Selection Processes.Marc Artiga - 2010 - Theoria 25 (2):197-209.
    In this paper I defend a teleological explanation of normativity, i. e., I argue that what an organism is supposed to do is determined by its etiological function. In particular, I present a teleological account of the normativity that arises in learning processes, and I defend it from some objections.
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  48. Learning to Imagine.Amy Kind - 2022 - British Journal of Aesthetics 62 (1):33-48.
    Underlying much current work in philosophy of imagination is the assumption that imagination is a skill. This assumption seems to entail not only that facility with imagining will vary from one person to another, but also that people can improve their own imaginative capacities and learn to be better imaginers. This paper takes up this issue. After showing why this is properly understood as a philosophical question, I discuss what it means to say that one imagining is better than another (...)
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  49. (1 other version)Learning from Learning from our Mistakes.Clayton Littlejohn - 2016 - In Martin Grajner & Pedro Schmechtig (eds.), Epistemic Reasons, Epistemic Norms, Epistemic Goals. De Gruyter. pp. 51-70.
    What can we learn from cases of knowledge from falsehood? Critics of knowledge-first epistemology have argued that these cases provide us with good reason for rejecting the knowledge accounts of evidence, justification, and the norm of belief. I shall offer a limited defense of the knowledge-first approach to these matters. Knowledge from falsehood cases should undermine our confidence in like-from-like reasoning in epistemology. Just as we should be open to the idea that knowledge can come from non-knowledge, we should be (...)
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  50. Learning from Learning from our Mistakes.Clayton Littlejohn - 2016 - In Martin Grajner & Pedro Schmechtig (eds.), Epistemic Reasons, Epistemic Norms, Epistemic Goals. De Gruyter. pp. 51-70.
    What can we learn from cases of knowledge from falsehood? Critics of knowledge-first epistemology have argued that these cases provide us with good reason for rejecting the knowledge accounts of evidence, justification, and the norm of belief. I shall offer a limited defense of the knowledge-first approach to these matters. Knowledge from falsehood cases should undermine our confidence in like-from-like reasoning in epistemology. Just as we should be open to the idea that knowledge can come from non-knowledge, we should be (...)
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